scholarly journals Fuzzy classifiers in cardiovascular disease diagnostics: Review

2020 ◽  
Vol 35 (4) ◽  
pp. 22-31
Author(s):  
I. A. Hodashinsky
Keyword(s):  
Artificial Intelligence ◽  
Medical Diagnosis ◽  
Classification Problem ◽  
Medical Diagnostics ◽  
Medical Systems ◽  
Classification Result ◽  
Biological Objects ◽  
Disease Diagnostics ◽  
Fuzzy Classifiers ◽  
Human Thinking

The complexity of biological objects makes the development of computerized medical systems a difficult algorithmic decision due to the natural uncertainty inherent in these objects. Human thinking is based on vague and approximate data that can be analyzed to form clear decisions. An exact mathematical model of biological objects may not exist in practice, or such a model may be too complex to implement. In this case, fuzzy logic is a suitable tool for solving the specified problem. The problem of medical diagnosis can be viewed as a classification problem. The article presents a literature review of the use of fuzzy classifiers in diagnostics of cardiovascular diseases. The main advantage of fuzzy classifiers in comparison with other artificial intelligence methods is the ability to interpret the resulting classification result. The review aims to expand the knowledge of various researchers working in the field of medical diagnostics.

scholarly journals Artificial intelligence using for medical diagnosis via implementation of expert systems

2021 ◽  
Vol 23 (1) ◽  
pp. 215-224
Author(s):  
B. N. Kotiv ◽  
Igor A. Budko ◽  
Igor A. Ivanov ◽  
Igor U. Trosko
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Medical Diagnosis ◽  
Intelligent Systems ◽  
Heuristic Methods ◽  
Limited Ability ◽  
Biomedical Technologies ◽  
Human Thinking ◽  
The 1960S ◽  
Almost All

Modern biomedical technologies development affords to provide the doctor with colossal amount of information about patients organism condition. However, the opportunity of using this data for medical diagnosis fully now is a distantive perspective only. The reason is a humans limited ability in assessment and interpretation this data arrays. The solution seems in artificial intelligence and expert systems wide introduction to medicine. Currently, almost all authors consider various options for constructing artificial neural networks as a way to implement artificial intelligence. This approach, which goes back to the fundamental theorem of A.N. Kolmogorov, the works of V.I. Arnold and Hecht-Nielsen [3], demonstrates excellent capabilities in a number of pattern recognition problems, which are reduced to revealing hidden details against the background of input noises. Much less often is mentioned such a method of modeling formal thinking as expert systems, which arose in the 1960s and then went into the shadows. Since the inception of cybernetics, computer programmers have tried to reproduce the mechanism of human thinking, that is, the task was to teach the computer to "think". The first known results in the field of creating and using intelligent systems were laid by the work of Norbert Wiener and G.S. Altshuller. At the same time, the creation of intelligent systems was reduced to the development of programs that solve problems using a variety of heuristic methods based on the property of human thinking to generalize.

Solving the Message Classification Problem in Voice Interaction Systems

Vestnik MEI ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. 132-139
Author(s):  
Ivan E. Kurilenko ◽  
◽  
Igor E. Nikonov ◽  
Keyword(s):  
Artificial Intelligence ◽  
Classification Problem ◽  
Subject Area ◽  
Text Messages ◽  
Case Based Reasoning ◽  
Short Text ◽  
Proposed Modification ◽  
Voice Interaction ◽  
Text Content ◽  
Case Based

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.

A moral analysis of intelligent decision-support systems in diagnostics through the lens of Luciano Floridi’s information ethics

Human Affairs ◽  
2021 ◽  
Vol 31 (2) ◽  
pp. 149-164
Author(s):  
Dmytro Mykhailov
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Medical Diagnosis ◽  
Moral Agency ◽  
Moral Agent ◽  
Well Being ◽  
Medical Diagnostics ◽  
Intelligent Decision ◽  
Luciano Floridi ◽  
Intelligent Decision Support

Abstract Contemporary medical diagnostics has a dynamic moral landscape, which includes a variety of agents, factors, and components. A significant part of this landscape is composed of information technologies that play a vital role in doctors’ decision-making. This paper focuses on the so-called Intelligent Decision-Support System that is widely implemented in the domain of contemporary medical diagnosis. The purpose of this article is twofold. First, I will show that the IDSS may be considered a moral agent in the practice of medicine today. To develop this idea I will introduce the approach to artificial agency provided by Luciano Floridi. Simultaneously, I will situate this approach in the context of contemporary discussions regarding the nature of artificial agency. It is argued here that the IDSS possesses a specific sort of agency, includes several agent features (e.g. autonomy, interactivity, adaptability), and hence, performs an autonomous behavior, which may have a substantial moral impact on the patient’s well-being. It follows that, through the technology of artificial neural networks combined with ‘deep learning’ mechanisms, the IDSS tool achieves a specific sort of independence (autonomy) and may possess a certain type of moral agency. Second, I will provide a conceptual framework for the ethical evaluation of the moral impact that the IDSS may have on the doctor’s decision-making and, consequently, on the patient’s wellbeing. This framework is the Object-Oriented Model of Moral Action developed by Luciano Floridi. Although this model appears in many contemporary discussions in the field of information and computer ethics, it has not yet been applied to the medical domain. This paper addresses this gap and seeks to reveal the hidden potentialities of the OOP model for the field of medical diagnosis.

scholarly journals Artificial Intelligence in Thyroid Field. A Comprehensive Review

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 4740
Author(s):  
Fabiano Bini ◽  
Andrada Pica ◽  
Laura Azzimonti ◽  
Alessandro Giusti ◽  
Lorenzo Ruinelli ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Cognitive Abilities ◽  
Medical Diagnostics ◽  
Critical Discussion ◽  
Research Field ◽  
Response To Treatment ◽  
Key Concepts ◽  
Mathematical Algorithms

Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g., machine learning and deep learning, as well as the recently developed research field of radiomics have noticeable potential to transform medical diagnostics. AI-based techniques applied to medical imaging allow to detect biological abnormalities, to diagnostic neoplasms or to predict the response to treatment. Nonetheless, the diagnostic accuracy of these methods is still a matter of debate. In this article, we first illustrate the key concepts and workflow characteristics of machine learning, deep learning and radiomics. We outline considerations regarding data input requirements, differences among these methodologies and their limitations. Subsequently, a concise overview is presented regarding the application of AI methods to the evaluation of thyroid images. We developed a critical discussion concerning limits and open challenges that should be addressed before the translation of AI techniques to the broad clinical use. Clarification of the pitfalls of AI-based techniques results crucial in order to ensure the optimal application for each patient.

scholarly journals Review of Artificial Intelligence

2020 ◽  
pp. 143-171
Author(s):  
K. P. V. Sai Aakarsh ◽  
Adwin Manhar
Keyword(s):  
Artificial Intelligence ◽  
Computational Intelligence ◽  
Medical Diagnosis ◽  
Computer Application ◽  
Knowledge Based Systems ◽  
Human Race ◽  
Knowledge Based ◽  
Ordinary Person ◽  
Digital Computers

Over many centuries, tools of increasing sophistication have been developed to serve the human race Digital computers are, in many respects, just another tool. They can perform the same sort of numerical and symbolic manipulations that an ordinary person can, but faster and more reliably. This paper represents review of artificial intelligence algorithms applying in computer application and software. Include knowledge-based systems; computational intelligence, which leads to Artificial intelligence, is the science of mimicking human mental faculties in a computer. That assists Physician to make dissection in medical diagnosis.

scholarly journals Applications of Non-Standard analysis in Topoi to Mathematical Neurosciences and Artificial Intelligence: Infons, Energons, Receptons (I)

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2048
Author(s):  
Ileana Ruxandra Badea ◽  
Carmen Elena Mocanu ◽  
Florin F. Nichita ◽  
Ovidiu Păsărescu
Keyword(s):  
Mathematical Modeling ◽  
Artificial Intelligence ◽  
Mathematical Model ◽  
Set Theory ◽  
Standard Analysis ◽  
New Methods ◽  
Internal Set ◽  
Human Thinking ◽  
Global Brain ◽  
Non Standard Analysis

The purpose of this paper is to promote new methods in mathematical modeling inspired by neuroscience—that is consciousness and subconsciousness—with an eye toward artificial intelligence as parts of the global brain. As a mathematical model, we propose topoi and their non-standard enlargements as models, due to the fact that their logic corresponds well to human thinking. For this reason, we built non-standard analysis in a special class of topoi; before now, this existed only in the topos of sets (A. Robinson). Then, we arrive at the pseudo-particles from the title and to a new axiomatics denoted by Intuitionistic Internal Set Theory (IIST); a class of models for it is provided, namely, non-standard enlargements of the previous topoi. We also consider the genetic–epigenetic interplay with a mathematical introduction consisting of a study of the Yang–Baxter equations with new mathematical results.

scholarly journals Prospects for Development of Artificial Intelligence in the Scientific Learning of the World

2019 ◽  
Vol 10 (4) ◽  
Author(s):  
Aleksey Stepanenko ◽  
Diana Stepanenko
Keyword(s):  
Artificial Intelligence ◽  
System Approach ◽  
Systematic Approach ◽  
Scientific Information ◽  
Existing Problems ◽  
The World ◽  
Human Thinking ◽  
Intelligence Development ◽  
Artificial Intelligence Systems ◽  
Scientific Learning

In the process of comprehending the prospects for the artificial intelligence development, the authors come to a conclusion that in the scientific learning of the world the problematic issues of the artificial intelligence are connected with problematic issues of recognizing the artificial intelligence systems and ordinary human thinking The article performs an analysis of the concepts of «intelligence» and «artificial intelligence», in the process of which the intelligence is viewed through a systematic approach in its broad sense. The purpose of the article is to present a number of conclusions about the levels of development of scientific studies of the problems under investigation, is there any reason to argue that attempts to implement the epistemological characteristics of thinking in modern artificial intelligence systems have not only been undertaken but also successful, and whether is it possible to talk about full transfer of the intellectual functions to the technical systems, endowing them with epistemological tools (in the context of the discussion about strong and weak versions of the artificial intelligence). The authors study the concept of «phenomenology of intelligence», the perception of intelligence in various historical eras by famous philosophers and scientists of other branches of knowledge; they identify the artificial intelligence as a special branch of science, analyze the existing problems in this field. In writing the article, they use the system approach, the theoretical analysis of and generalization of the scientific information, the historical, predicted, critical and dialectical methods of investigation.

Development of algorithms that simulate the solution of a problem by a person

2022 ◽  
Vol 1 ◽  
pp. 01006
Author(s):  
Iurii V. Filatov
Keyword(s):  
Artificial Intelligence ◽  
High Speed ◽  
Separate Study ◽  
Human Actions ◽  
History Of ◽  
Human Thinking ◽  
Problem Comparison ◽  
The Way

Some algorithms, which are often based on the use of elements of higher mathematics, possessing high speed and compact coding in algorithmic languages, are poorly mastered by most students. It can be assumed that this is due to the difficulty of presenting the principles of their work in the form of human actions in ordinary situations. Thus, a certain contradiction arises between the way of solving the problem that a person resorts to without using a computer and the way we force our computer to solve this problem. Comparison of the process of explaining algorithms speaks in favor of algorithms imitating human thinking. The discussion of the advantages of the algorithms themselves is beyond the scope of this article and undoubtedly deserves a separate study. If artificial intelligence is created, then its creator or creators will certainly be ranked among the outstanding geniuses in the history of civilization, no matter what algorithms it uses. However, so far there is no one to solve problems for us and create algorithms, so we will use all available means and try to teach this to children.

Artificial Intelligence in Medical Science

2014 ◽  
pp. 11-23 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Decision Making ◽  
Signal Processing ◽  
Expert System ◽  
Knowledge Base ◽  
Medical Diagnosis ◽  
Medical Science ◽  
Inference Engine ◽  
Medical Decision

Applying Artificial Intelligence (AI) for increasing the reliability of medical decision making has been studied for some years, and many researchers have studied in this area. In this chapter, AI is defined and the reason of its importance in medical diagnosis is explained. Various applications of AI in medical diagnosis such as signal processing and image processing are provided. Expert system is defined and it is mentioned that the basic components of an expert system are a “knowledge base” or KB and an “inference engine”. The information in the KB is obtained by interviewing people who are experts in the area in question.

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